Sustainable Energy Resources Research Articles

Dielectric Elastomer Generators: Recent Advances in Materials, Electronic Circuits, and Prototype Developments

The ongoing climate crisis requires innovative methods to maximize renewable and sustainable energy resources. There have been advancements in harvesting energy from ambient motions such as wind, ocean waves, and human movements. Dielectric elastomer generators (DEGs) are a promising option for energy harvesting due to their high energy density and compatibility with low‐frequency oscillations. This review provides an in‐depth overview of DEGs, including electroactive materials, electromechanical characterization, electronics for harvesting, interfacing circuits, prototypes, and challenges. DEGs have the potential to play a significant role in decarbonizing energy for both small‐ and large‐scale applications using ambient energy sources.

A Mathematically Optimized Design Solution for Structure of PEMFC Catalyst Layer Based on a Two-Phase Flow Model

Abstract Proton exchange membrane fuel cells (PEMFCs) have emerged as a promising solution as the world is moving toward sustainable energy resources. However, in order to compete economically with existing technologies, further improvements in performance are necessary. Mathematical modeling and optimization are viable tools for designing better PEMFCs. This study aims to provide a framework for topological optimization of the electrode structure, with the ultimate goal of enhancing cell performance. To achieve this, a two-phase flow model of PEMFC is developed to characterize the cell performance. The model is then coupled with a topology optimization technique, which is the main focus of the present work, to seek an optimized constituent distribution in the catalyst layer. Results indicate that an electrode with a heterogeneous structure can enhance the overall cell performance by balancing various transport and rate processes. The optimized designs are investigated for various key factors, including effective diffusivity, effective conductivity, and liquid water management, to demonstrate how an optimized design can be advantageous.

Unravelling the electrochemical characteristics and sodium storage mechanism of pistachio shell derived hard carbon as high plateau capacity anodes by operando Raman spectroscopy and full cell demonstration

Hard carbon has emerged as a highly promising material for negative electrode in sodium-ion batteries (SIBs). This study focuses on the synthesis of an anode material through the pyrolysis of Pistachio shells, a commonly available nut waste, at different temperatures ranging from 900° to 1400°C. The material pyrolyzed at 1400 °C exhibits a remarkable reversible discharge capacity of 302 mAhg−1 and plateau capacity of 223 mAhg−1 at a current rate of 10 mAg−1, displaying stable cyclic performance and an impressive 80% capacity retention after 500 cycles at 200 mAg−1. The morphological, structural, and surface chemical characteristics of the cycled hard carbon anode materials were examined through ex-situ FE-SEM, XRD, and XPS analyses. Furthermore, the sodiation and desodiation mechanisms of the synthesized hard carbon were investigated using operando Raman Spectroscopy. The diffusion kinetics parameters were determined by Electrochemical Impedance Spectroscopy (EIS) and CV analyses. This study underscores the potential of Pistachio shells as a promising precursor for the synthesis of carbonaceous anode for SIBs, employing a straightforward one-step pyrolysis process. The excellent electrochemical performance, along with the ease of material sourcing and synthesis, places this nutty waste as a promising, sustainable and clean energy resource option for advancing sodium-ion battery technology.

Photovoltaic Modules’ Cleaning Method Selection for the MENA Region

Photovoltaic (PV) systems are important components of the global shift towards sustainable energy resources, utilizing solar energy to generate electricity. However, the efficiency and performance of PV systems heavily rely on cleanliness, as dust accumulation can significantly obstruct their effectiveness over time. This study undertook a comprehensive literature review and carried out multiple interviews with experts in the PV systems field to propose a map for selecting the optimal PV cleaning method for PV systems within MENA region. These factors, covering meteorological conditions, the local environment, PV system design, module characteristics, dust deposition attributes, exposure time to dust, and socio-economic and environmental considerations, were employed as criteria in a Multi-Criteria Decision-Making (MCDM) model, specifically, an Analytic Network Process (ANP). The results indicate that partially automated cleaning is the most suitable method for existing utility-scale PV projects in the MENA region. The findings provide robust guidelines for PV system stakeholders, aiding informed decision-making and enhancing the sustainability of PV cleaning processes.

Two-dimensional BiSbTeX2 (X = S, Se, Te) and their Janus monolayers as efficient thermoelectric materials.

Today, there is a huge need for highly efficient and sustainable energy resources to tackle environmental degradation and energy crisis. We have analyzed the electronic, mechanical and thermoelectric (TE) characteristics of two-dimensional (2D) BiSbTeX2 (X = S, Se and Te) and Janus BiSbTeXY (X/Y = S, Se and Te) monolayers by implementing first principles simulations. These monolayers' dynamic stability and thermal stability have been demonstrated through phonon dispersion spectra and ab initio molecular dynamics (AIMD) simulations, respectively. The band structure of these monolayers can be tuned by applying uniaxial and biaxial strains. The investigated lattice thermal conductivity (κl) for these monolayers lies between 0.23 and 0.37 W m-1 K-1 at 300 K. For a more precise calculation of the scattering rate, we implemented electron-phonon coupling (EPC) and spin-orbit coupling effects to calculate the transport properties. For p(n)-type carriers, the power factor of these monolayers is predicted to be as high as 2.08 × 10-3 W m-1 K-2 and (0.47 × 10-3 W m-1 K-2) at 300 K. The higher thermoelectric figure of merit (ZT) of p-type carriers at 300 K is obtained because of their very low value of κl and high power factor. Our theoretical investigation predicts that these monolayers can be potential candidates for fabricating highly efficient thermoelectric power generators.

Synergetic Combination of Bio‐Electrolytes and Bio‐Fluidic Channels as a Novel Resource of Sustainable Energy

AbstractExploration for sustainable energy resources is essential to minimize the dependence on fossil fuels and to improve environmental parameters. Here, the possibility of utilizing bio‐waste‐derived electrolytes as an electrical energy resource by placing them across semipermeable membranes prepared through parallel stacking of coir fibers is examined. The nanofluidic membrane (d‐CF‐V) prepared by modifying the inner walls of the bio‐fluidic channels with atomically thin layers of vanadium pentoxide (VO) shows excellent perm‐selectivity (t+ = 0.87, with 1000‐fold concentration difference) and electricity conversion efficiency (≈ 28.2%). With simulated sea and river water, the d‐CF‐V yields output energy up to 2.4 W m−2, similarly with mineral acid bases (0.5 m HCl and 0.01 m NaOH), the d‐CF‐V shows an energy output of 11.8 W m−2. The sun‐dried Garcinia morella (Kuji thekera), and charred peels of Musa balbisiana (banana) are used as sustainable sources of bio‐electrolytes, which in combination with permselective d‐CF‐V yielded a power density of ≈1.4 W m−2. By replacing standard Ag/AgCl electrodes with nanomaterials exhibiting contrasting charge transfer activities, oxidized carbon nanotube membrane (o‐CNT) and polyaniline (PANI) membrane the output voltage is enhanced from –127 to –568 mV and current output is increased from 10.2 to 51.5 µA.

Rheological behavior of deep eutectic solvent promoted methane hydrate formation

Natural gas hydrates are recognized as a crucial and sustainable energy resource. The formation, dissociation, and flow properties of CH4 hydrate from deep eutectic solvents (DESs) are investigated using a high-pressure rheometer. In this work, rheological experiments are performed using two DESs namely, tetrabutylammonium bromide + ethylene Glycol (TBAB + EG, DES1) and methyltriphenylphosphonium bromide + ethylene Glycol (MTPB + EG, DES2) at 1 wt% concentration, 274 K temperature and 8 MPa pressure. The hydrate formation starts around 1.7 h for DES1 and around 4 h for DES2. Pressure and viscosity of the slurry are analyzed while methane hydrate forms and dissociates. The pressure drop experienced during hydrate formation is roughly 1.4 MPa for DES1 and 1.7 MPa for DES2. Further, viscosity profiles are analyzed for both DESs with varying shear rate. The viscosity gradually decreases as the shear rate increases. At equilibrium conditions of pure CH4, a spike is observed during dissociation. The rheological data is further analyzed with Cross model to validate the shear-thinning behavior of methane hydrate.

Effect of Ultrasonic Waves on Aspire Biodiesel and Comparison of Its Properties with Petroleum Diesel

This study aimed to determine the effect of ultrasonic sound waves on modifying the chemical structure of biodiesel to bring its physical properties closer to petroleum diesel. In this direction, safflower oil was selected because its fatty acid composition is similar to fatty acid esters of petroleum diesel and is a sustainable source. Refined safflower oil, the free fatty acid content of which was determined, was reacted with methanol under NaOH catalyst to perform the transesterification reaction. After biodiesel production, samples were incubated in an ultrasonic bath for 60, 120, and 180 minutes. FTIR, density, free fatty acid content, flash point, viscosity, and cloud point analyses investigated the effect of incubation times on biodiesel's chemical structure and properties. FTIR spectra showed that ultrasonic sound waves partially decomposed fatty acid methyl esters and increased the number of volatile components in biodiesel. The flash point of biodiesel has been associated with a decrease of 89°C, and the low flash point is expected to increase fuel efficiency. Kinematic viscosity values were measured in the 3.4583-3.5115 mm²/s range, and density values were measured in the 0.8820-0.8872 g/ml range. These values show that biodiesel complies with national and international standards. As a result, the ultrasonic bath process applied to biodiesel showed a similar result to chemical modification methods by affecting the structure of fatty acid chains. Thus, it brought the physical properties of biodiesel closer to petroleum diesel. It is seen that this method is a more efficient alternative for biodiesel production because it does not use additional chemicals, and the process is faster. In conclusion, by increasing the production of the drought-resistant safflower plant, sustainable energy resources will be contributed, while its waste can be evaluated as animal feed. Ultrasonicated safflower biodiesel can also be used as an efficient, environmentally and mechanically friendly alternative fuel source.

Ag-Mediated Growth of Au/Ag-Cu Ternary Heterostructures for Selective Electrochemical CO2 Reduction.

Copper (Cu)-based nanocatalysts play crucial roles in the electrochemical CO2 reduction reaction (ECO2RR) for sustainable energy resources. Particularly, Cu-based nanostructures incorporating Au and Ag are promising, offering enhanced activity, selectivity, and stability. However, precise control over the structure and composition of heterostructures remains challenging, hindering the development of highly efficient catalysts. Herein, we present a silver (Ag) transition-layer-mediated approach to synthesize ternary heterostructures with two specific morphologies, namely, Au/Ag-Cu-side and Au/Ag-Cu-tip, which exhibit different Ag-Cu interface epitaxial patterns. The two heterostructures achieve high C2 product selectivity in ECO2RR. Especially, the Au/Ag-Cu-side structure achieves 50.3% C2 selectivity with 35.5% ethanol, while the tip structure shows higher ethylene selectivity. Our study reveals the impact of the Ag layer in directing deposition sites on heterostructure growth and further facilitating the design of multicomponent Cu-based catalysts with enhanced structural integrity and ECO2RR performance.

Novel decision making approach for sustainable renewable energy resources with cloud fuzzy numbers

Decision making approaches depending on the assessments of individual decision makers produce inaccurate results due to the existence of multiple uncertainties. To model intrapersonal uncertainty, interpersonal uncertainty and randomness in decision making assessments, this research study proposes a novel approach by integrating linear and non-linear type of fuzzy numbers with cloud model theory using novel technique of computing entropy of these fuzzy numbers. A novel mathematical model known as cloud fuzzy numbers is introduced using the concepts of fuzzy numbers and cloud theory. The self-evaluated relative weights of experts are computed using a non-linear optimization method which is based on maximum deviation method and Lagrange multipliers of cloud fuzzy numbers. The new cloud fuzzy numbers are then combined with CODAS (combinative distance based assessment) approach that is based on the largest Euclidean and Taxicab distances for the selection of suitable criteria. Firstly, the linguistics evaluations are converted into the fuzzy numbers and then cloud fuzzy numbers using formulae of expectation and entropy ensuring that the obtained interval cloud values follows a normal distribution. Secondly, the cloud fuzzy weighted arithmetic averaging operator is used to aggregate cloud fuzzy numbers using the self-evaluated fuzzy weights Thirdly, the assessment score is determined to rank the alternatives by computing the distance between normalized weighted matrix and the negative ideal solution. Finally, a case study is discussed for the selection of best renewable energy resource in Turkey to elaborate the significance of the proposed research. The convergence and accuracy of the proposed model is proved with certain mathematical and theoretical results.

Modeling of Energy Usage Intensity Based on West Java Region Conditions Using Dynamic Systems Approach

Abstract West Java is a region in Indonesia experiencing significant population growth and economic activity, leading to a substantial increase in energy demand and presenting challenges for sustainable energy resource management. Energy is fundamental to economic and social activities, and efficient, sustainable management is essential for balancing economic growth with environmental preservation. Modeling energy usage intensity is crucial for understanding the dynamics of energy consumption and its influencing factors. This study aims to develop a model that accurately represents energy consumption patterns in West Java using a dynamic systems approach. The study utilizes Causal Loop Diagrams (CLD) and Stock Flow Diagrams (SFD) to systematically map and model the intricate dynamics of the energy system, providing a comprehensive understanding of the interactions and influences among various factors. The model was validated by comparing its outputs with historical data and calculating a Mean Absolute Percentage Error (MAPE). This enhances confidence in the analyses and recommendations derived from the model, making it a valuable tool for understanding and influencing energy usage patterns in West Java. In conclusion, this study not only provides deep insights into energy consumption in West Java but also offers practical approaches for improved energy management, supporting sustainable development and environmental protection in the region.

Exploring the convergence of Metaverse, Blockchain, Artificial Intelligence, and digital twin for pioneering the digitization in the envision smart grid 3.0

The ongoing evolution of the Metaverse, digital twin (DT), artificial intelligence (AI), and Blockchain technologies is fundamentally transforming the utilization of sustainable energy resources (SERs) within smart grids (SGs), ushering in the era of smart grid 3.0 (SG 3.0). This paradigm shift presents unprecedented opportunities to establish robust and sustainable energy trading frameworks between consumers and utilities within the SG 3.0 environment. The integration of DT, AI, and Blockchain technologies in the context of the Metaverse’s smart grids, facilitated by optimized communication protocols, represents a transformative approach. AI models play a pivotal role in predictive energy trading analysis, while DT assumes a crucial role in effectively managing diverse SERs within SGs. Simultaneously, Blockchain technology holds the potential to create a trusted and decentralized environment, laying the foundation for an energy trading system within the SG 3.0 universe of the Metaverse. This visionary convergence of DT and Blockchain sets the stage for a futuristic paradigm in SGs, establishing a robust energy trading and management foundation. This paper embarks on exploring uncharted research paths and unlocking new dimensions by surveying and delving into the convergence of the Metaverse, Blockchain, AI, and DT. Its primary objective is to drive the digitization of SERs within SGs, to revolutionize energy systems. The envisioned SG 3.0 represents a significant leap by amalgamating cutting-edge technologies in sustainable energy, paving the way for revolutionary advancements in SGs’ digitization, which aligns with and contributes to achieving the sustainable development goals outlined by the United Nations.

Measuring Household Thermal Discomfort Time: A Japanese Case Study

This study proposes a metric to measure households’ discomfort related to thermal consumption time (hereafter referred to as t-discomfort). This metric relies on an ideal thermal consumption and calculates the gap between the usage times of thermal devices in vulnerable households compared to the ideal household. The t-discomfort is quantified using thermal data collected from 1298 households in the Tokyo and Oita prefectures in Japan. To create the ideal usage times of thermal devices, households are categorized into three clusters—Vulnerable (Vu), Semi-vulnerable (SVu), and Invulnerable (IVu)—based on their energy poverty ratio, and t-discomfort is subsequently calculated for each group. The IVu households are used as the ideal reference point for measuring thermal device usage in the other two categories. The findings of the study indicate that energy poverty does not necessarily lead to t-discomfort. Interestingly, the consumption time of heating devices among Vu households in both prefectures is longer than that of IVu households, despite the high energy prices. Conversely, SVu households, which do not experience severe energy poverty, tend to sacrifice their comfort by reducing their thermal consumption time. Additionally, the consumption time of cooling devices among Vu households in Oita is longer than that of IVu households, whereas in Tokyo, it is shorter. Two treatment strategies are evaluated to mitigate thermal discomfort in households without compromising resource availability. The first strategy integrates the thermal device consumption time with Japan’s current regulated time-of-use rates plan (daytime and nighttime). The results propose a three-tiered tariff plan (off-peak, mid-peak, and peak) to reduce the energy cost burden for Vu households. The second strategy recommends the installation of 12 rooftop solar panels for households in Tokyo and 11 panels for households in Oita. This strategy aims to maintain thermal comfort via a sustainable natural energy resource while minimizing energy costs.

The asymmetric nexus between energy transition and its drivers: New evidence from China

The unpredictable surge in global warming and climatic issues urges serious efforts internationally to meet the Paris Agreement to keep the global temperature below 2 °C. Therefore, a sustainable solution is necessary for the future, as most regions are still under high pollution and carbon regimes borne by traditional sources of fuels. In this context, transitioning energy resources from conventional to more clean and sustainable energy resources is a key international political agenda. This study has investigated the asymmetric relationship of energy transition and its drivers in the case of China. The study employed time series data from 1989 to 2022 and adopted the nonlinear ARDL test. Through bounds testing, this study confirmed the existence of long-run asymmetric co-integration between the policy instruments. In the long and short run, the positive shocks of environmental technology augmented the asymmetric relationship with energy transition. However, it is interesting to observe that the positive shocks of green finance and trade openness has adverse effects on energy transition in the long run. Though, in the short run, a positive shock of trade openness improves the energy transition process. This study recommends policies to help policymakers and other stakeholders attain the SDG 7 goals.

Lignocellulosic Biomass Decomposition and Bioconversion

Lignocellulosic biomass (LCB) offers numerous advantages as a sustainable energy resource, such as its abundance, degradability, environmental compatibility, non-toxic nature, and cost-effectiveness [...]

A comparative study of the impact of the CO2 properties on the thermal output of a geothermal well

The problem of growing carbon footprint calls for the exploitation of cleaner and sustainable energy resources. Being clean, renewable, and abundant, Geothermal energy emerges as an ideal solution. However, existing geothermal power plants are extremely sparse and can be globalized only heat extraction from deep rocks becomes feasible, which is challenging due to the absence of power fluid and inaccessibility of geothermal heat at high depths. In this study, an effort is made to understand and improve the reservoir heat extraction through a geothermal well from deep formations. It also evaluates the viability of utilizing CO2 as energy transfer fluid. Our approach involves developing unified thermodynamic property models for CO2, covering the entire spectrum from vapor to supercritical phases and eliminating the need for piecewise correlations and look-up tables. A coupled well-reservoir model is employed to analyze the impact of fluid properties on the thermal output of a geothermal well. The results show that the thermal output is highly sensitive to the fluid properties, implying the importance of accurate thermodynamic models in assessing the economics of the entire geothermal project.

Sustainable energy harvesting from medical waste: Utilizing discarded ointment tubes in triboelectric nanogenerators

Medical waste management is a common global issue that causes environmental pollution and poses significant health risks. The present study introduces a sustainable approach to addressing this issue by utilizing discarded medical ointment tubes to fabricate Triboelectric Nanogenerators (TENGs) for energy harvesting applications. The discarded metallic ointment tubes with epoxy resin coating inside simplify the TENG fabrication. The fabricated metallic ointment tube-based TENG produces a maximum output voltage of ∼ 405 V and a current of ∼ 82 µA, with a power density of 658 mW/m2. Further, TENG was utilized to power 480 LEDs and portable electronic devices with the help of an energy management system. The present work highlights the potential of transforming medical waste into sustainable energy resources.

Superlight Ambient Temperature Reversible Hydrogen Storage Media Based on Alkali and Alkali Earth Metal-Functionalized 2D Square-Octagon BCN Monolayer.

Energy has always been the engine of human beings; however, because of the environmental pollution caused by traditional fossil fuels, the development of more sustainable energy resources is urgently needed. The hydrogen storage medium is essential for its realization. Here, we introduce a hydrogen storage material, a two-dimensional (2D) square-octagon BCN (SO-BCN) monolayer, composed of lightweight elements (B, C, and N) and strategically functionalized with alkali and alkali earth metal atoms (Li, Na, Mg, and K). Notably, Li@SO-BCN and Mg@SO-BCN exhibit exceptional reversible hydrogen storage capabilities, surpassing the DOE standard of 5.5 wt %, with gravimetric capacities of 7.129 wt % and an impressive value of 11.656 wt %, alongside low adsorption energies of -0.21 eV/H2 and -0.268 eV/H2 at room temperature, respectively. Our investigation, which combines analysis of the atomic structure, electronic structure, and hydrogen process, reveals distinct mechanisms at play: Li activates the substrate, creating additional adsorption sites on the SO-BCN monolayer. Compared with Li, the functionalization of Mg atoms not only activates SO-BCN via charge transfer but also allows Mg2+ to act as a potent attractor for H2 molecule adsorption. This work provides both promising candidates for future hydrogen storage media based on 2D monolayers and a design paradigm for next-generation hydrogen storage materials, emphasizing the synergy of electron-donating species, substrate activation, and hierarchical porous structures.

Toward sustainable energy resource: Integrated concentrated photovoltaic and membrane distillation systems for fresh water and electricity production

This study introduces and evaluates a novel Concentrated Photovoltaic (CPV)-assisted Direct Contact Membrane Distillation (DCMD) system, examining its efficiency and energy output under varying operational conditions. A Computational Fluid Dynamics (CFD) model, validated with experimental data, assesses the system's performance at different concentration ratios ranging from 1x to 10x and 25x to 100x, flow patterns (counterflow and parallel flow) at different Reynolds numbers (30–1200). This study investigates the seasonal performance of the CPV-DCMD system, providing valuable insights into its reliability and sustainability throughout the year. Results show increased mass flux and electric power with higher concentration ratios, especially at lower Reynolds numbers. In the counter-flow arrangement, the mass flux increases notably under specific conditions, while seasonal analysis reveals peak flux during summer and autumn afternoons. Electric power output follows a consistent trend across seasons, with high output observed during noon hours. The study demonstrates the system's energy efficiency, with notable energy gain compared to consumption across diverse operational conditions. Overall, the findings provide insights into optimizing the performance of CPV-assisted DCMD systems for sustainable energy generation and water desalination applications.

Evaluation and benchmarking of research-based microgrid systems using FWZIC-VIKOR approach for sustainable energy management

Microgrid (MG) is one of the technologies considered in the direction of providing green and sustainable energy resources for local communities. Ensuring the best performance of these MG technologies requires extensive research to provide the most efficient system. Research-based microgrids (RB-MGs) play a vital role in the development of green energy platforms, as microgrid applications vary according to different scenarios and locations. Selecting the best research-based microgrid ensures providing local communities and stakeholders with well-tested and examined MG systems. Assessing research-based microgrid systems (RB-MG) for sustainable green applications poses a challenging multi-attribute decision-making (MADM) problem. These complexities encompass the consideration of several evaluation criteria, the relative importance of these criteria, variations in data, and the inherent trade-offs and conflicts between these factors. Crisp and definite values to evaluate the research-based microgrids could not be found despite a comprehensive investigation. In this regard, appraisals and opinions of experts and professionals in providing sustainable energy with vast knowledge and experience in assessment, selection, installation, and operation were addressed as data. A novel decision-making model was developed to evaluate and select the most proper RB-MG system by processing these data. This study proposes an integrated MADM modelling approach using Fuzzy Weighted with Zero Inconsistency (FWZIC) method in conjunction with the Vlse-kriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) method. The underlying process starts with constructing a decision matrix (evaluation criteria intersectioned with RB-MGs). Then, evaluation criteria are weighted using FWZIC, and the RB-MGs are ranked for each category using VIKOR. The results derived from FWZIC weights provide valuable insights. Key criteria such as 'installed power (KW)' and 'storage capacity (C3)' show notable values of 0.159 and 0.151, respectively, underscoring their importance in identifying optimal RB-MGs. These weights and alternatives were used to rank the highest RB-MG, which is LIER-CIRCE of the average PV power group, and Ormazabal from the 'Highest PV Power' group. Ormazabal obtained the lowest Qi (0.426). For the average PV power group, alternative number 7 (Atenea Centre) ranked as the best alternative with the lowest Qi among other RB-MGs in the same group (0.158107). Comparative assessments with various MCDM methods reveal strong correlations with TOPSIS and MABAC, but negative correlations with MAIRA. Additionally, there is a statistical difference in grouping by PV installed power (KW) or MPC.